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Temporary materialized views in cloud data warehouses through a web service

机译:通过Web服务在云数据仓库中的临时物化视图

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Cloud Computing provides a flexible environment for customers to host and process their information through an outsourced infrastructure. This information was habitually located on local servers. Many applications dealing with massive data is routed to the cloud. Data Warehouse (DW) also benefits from this new paradigm to provide analytical data online and in real time. DW in the Cloud benefited of its advantages such flexibility, availability, adaptability, scalability, virtualization, etc. Improving the DW performance in the cloud requires the optimization of data processing time. The classical optimization techniques (indexing, materialized views and partitioning) are still essential for DW in the cloud. However, the DW is partitioned before being distributed across multiple servers (nodes) in the Cloud. When query containing multiple joins or ask voluminous data stored on multiple nodes, inter-node communication increases and consequently the DW performance degrades. In this paper, we propose an approach for improving the performance of DW in the cloud. Our approach is based on selection of temporary materialized views through a web service. For this purpose we use an algorithm allows to identify the queries list sent to the DW, and adds a materialized view for each new costly frequent query. This technique is based on managing a temporary materialized views in order to optimize the frequent queries load by respecting the total cost. An experimental study on a cloud DW is carried out and a comparative tests show the satisfaction of our approach.
机译:云计算为客户提供了一个灵活的环境,可通过外包基础架构托管和处理其信息。该信息通常位于本地服务器上。许多处理海量数据的应用程序都路由到云中。数据仓库(DW)还受益于这种新的范例,可以在线和实时提供分析数据。云中的DW受益于其灵活性,可用性,适应性,可伸缩性,虚拟化等优势。提高云中的DW性能需要优化数据处理时间。对于云中的DW而言,经典的优化技术(索引,实例化视图和分区)仍然至关重要。但是,DW先进行分区,然后再分布在云中的多个服务器(节点)上。当查询包含多个联接或询问存储在多个节点上的大量数据时,节点间的通信会增加,因此DW性能会降低。在本文中,我们提出了一种改善云中DW性能的方法。我们的方法基于通过Web服务选择的临时物化视图。为此,我们使用一种算法来识别发送到DW的查询列表,并为每个新的代价高昂的频繁查询添加一个物化视图。该技术基于管理临时的物化视图,以便通过考虑总成本来优化频繁查询的负载。对云DW进行了实验研究,并进行了比较测试,结果表明我们的方法令人满意。

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